The Optimal Dataset Scale (ODS), where one chooses the optimal threshold for the entire dataset before applying the F1 score, the Optimal Image Scale (OIS), where one chooses the optimal threshold per-image before using the F1 score, are two metrics to evaluate the quality of edge detection algorithm on the whole dataset.
The OIS is always a bit better than the ODS, since it considers the best scale for each image. The OIS corresponds to the optimistic situation where we have the optimal threshold for each image of the dataset. For more information about these classical measures for edge
detection, we refer to [1]}[2]}.
